Abstract: A state-estimator for the estimation or initialization of the state of a discrete-time state-space dynamical model based on sensor measurements of the model output, comprising fitting a continuous-time function to acquired sensor measurement data-points of each model output, and subsequently sampling the continuous time function at exactly the sample-period of the state-space dynamic model for which the state is being estimated or initialized, in order to construct a model state via a synthesized output trajectory.

Abstract: A state-estimator for the estimation or initialization of the state of a discrete-time state-space dynamical model based on sensor measurements of the model output, comprising fitting a continuous-time function to acquired sensor measurement data-points of each model output, and subsequently sampling the continuous time function at exactly the sample-period of the state-space dynamic model for which the state is being estimated or initialized, in order to construct a model state via a synthesized output trajectory.

Abstract: A machine for processing continuous glucose monitoring data and issuing an alert if hypoglycemia is imminent has three modules: (a) a pre-processing module that receives and modulates continuous glucose monitoring data by reducing noise and adjusting for missed data points and shifts due to calibration; (b) a core algorithm module that receives data from the pre-processing module and calculates a rate of change to make a hypoglycemia prediction, and determine if hypoglycemia is imminent; and (c) an alarm mode module that receives data from the core algorithm and issues an audio or visual alert or warning message or a negative feedback signal to an insulin delivery device if hypoglycemia is imminent.

Abstract: The disclosure relates to drug delivery and maintaining multiple defined physiological zones using model predictive control.

Abstract: A machine for processing continuous glucose monitoring data and issuing an alert if hypoglycemia is imminent has three modules: (a) a pre-processing module that receives and modulates continuous glucose monitoring data by reducing noise and adjusting for missed data points and shifts due to calibration; (b) a core algorithm module that receives data from the pre-processing module and calculates a rate of change to make a hypoglycemia prediction, and determine if hypoglycemia is imminent; and (c) an alarm mode module that receives data from the core algorithm and issues an audio or visual alert or warning message or a negative feedback signal to an insulin delivery device if hypoglycemia is imminent.

Abstract: Methods, devices, algorithms, and systems controlling insulin delivery employ velocity-weighting. Predicted glucose outcomes are penalized with a cost modulated by a factor that is a function of the glucose velocity, wherein glucose outcomes are penalized increasingly less for increasingly negative glucose velocities, when glucose level is high, and/or wherein a hyperglycemic glucose value that is already converging to the euglycemic zone results in less corrective action by the controller than were the hyperglycemic state steady.

Abstract: A state-estimator for the estimation or initialization of the state of a discrete-time state-space dynamical model based on sensor measurements of the model output, comprising fitting a continuous-time function to acquired sensor measurement data-points of each model output, and subsequently sampling the continuous time function at exactly the sample-period of the state-space dynamic model for which the state is being estimated or initialized, in order to construct a model state via a synthesized output trajectory.

Abstract: A glucose rate increase detector (GRID) for use in an artificial pancreas (AP), wherein the GRID detects in a person persistent increases in glucose associated with a meal, and either triggers a meal bolus to blunt meal peak safely, during closed-loop control, or alerts the person to bolus for a meal, during open-loop control.

Abstract: Disclosed are systems and methods for variable dose glucagon delivery without the need to manually reconstitute the glucagon. These systems and methods mat be utilized with or without a separate continuous glucose monitor. The variability of the dose may be determined manually by the user, caregiver or responder, or by preprogrammed algorithms utilizing the input from an external sensor such as a continuous glucose monitor.

Abstract: A model-based control scheme consisting of either a proportional-integral-derivative (IMC-PID) controller or a model predictive controller (MPC), with an insulin feedback (IFB) scheme personalized based on a priori subject characteristics and comprising a lower order control-relevant model to obtain PID or MPC controller for artificial pancreas (AP) applications.

Abstract: A controller for an artificial pancreas for automated insulin delivery to patients with type 1 diabetes mellitus (T1DM) that enforces safe insulin delivery throughout both day and night, wherein the controller employs zone model predictive control, whereby real-time optimization, based on a model of a human's insulin response, is utilized to regulate blood glucose levels to a safe zone, and time-dependent zones that smoothly modulate the controller correction based on the time of day, wherein the controller strategically strives to maintain an 80-140 mg/dL glucose zone during the day, a 110-220 mg/dL zone at night, and a smooth transition of 2 hour duration in between.

Abstract: A method, computer implemented method and associated apparatus for the management of diabetes comprises utilizing zone model predictive control (Zone-MPC) to control delivery of an insulin or insulin analog within a zone of desired values.

Abstract: The disclosure relates to drug delivery and maintaining multiple defined physiological zones using model predictive control.

Abstract: A machine for processing continuous glucose monitoring data and issuing an alert if hypoglycemia is imminent has three modules: (a) a pre-processing module that receives and modulates continuous glucose monitoring data by reducing noise and adjusting for missed data points and shifts due to calibration; (b) a core algorithm module that receives data from the pre-processing module and calculates a rate of change to make a hypoglycemia prediction, and determine if hypoglycemia is imminent; and (c) an alarm mode module that receives data from the core algorithm and issues an audio or visual alert or warning message or a negative feedback signal to an insulin delivery device if hypoglycemia is imminent.

Abstract: A method, computer implemented method and associated apparatus for the management of diabetes is provided.

Abstract: A system for predicting hypoglycemia based on continuous blood glucose monitor values is provided. The hypoglycemia detection algorithm is a set of individual alarms that are combined through a voting system into one combined alarm. The system could have five components and an overall voting algorithm that produces a binary alarm outcome depending on the number of constituent algorithms that report an alarm. A controller system automatically shuts off the insulin pump when pending or real hypoglycemia has been reached. The algorithms operate in a closed loop and automatically take action when the subject is asleep.